Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma

Asthma is a common complex disease with susceptibility defined through an interplay of genetic and environmental factors. Responsiveness to asthma treatment varies between individuals and is largely determined by genetic variability. The polygenic score (PGS) approach enables an individual risk of asthma and respective response to drug therapy. PGS models could help to predict the individual risk of asthma using 26 SNPs of drug pathway genes involved in the metabolism of glucocorticosteroids (GCS), and beta-2-agonists, antihistamines, and antileukotriene drugs associated with the response to asthma treatment within GWAS were built. For PGS, summary statistics from the Trans-National Asthma Genetic Consortium GWAS meta-analysis, and genotype data for 882 individuals with asthma/controls from the Volga-Ural region, were used. The study group was comprised of Russian, Tatar, Bashkir, and mixed ethnicity individuals with asthma (<i>N</i> = 378) aged 2-18 years. and individuals without features of atopic disease (<i>N</i> = 504) aged 4-67 years from the Volga-Ural region. The DNA samples for the study were collected from 2000 to 2021. The drug pathway genes' PGS revealed a higher odds for childhood asthma risk (<i>p</i> = 2.41 × 10<sup>-12</sup>). The receiver operating characteristic (ROC) analysis showed an Area Under the Curve, AUC = 0.63. The AUC of average significance for moderate-to-severe and severe asthma was observed (<i>p</i> = 5.7 × 10<sup>-9</sup>, AUC = 0.64). Asthma drug response pathway gene variant PGS models may contribute to the development of modern approaches to optimise asthma diagnostics and treatment.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2024-12-26
DOI
https://doi.org/10.3390/ijms26010103
Citations
1
Primary Topic
Asthma and respiratory diseases
Type
article
Field-Weighted Citation Impact
0.33

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article

Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma

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article

Evaluation of Polygenic Risk Score for Prediction of Childhood Onset and Severity of Asthma

Zhanna Balkhiyarova, Inga Prokopenko, I. R. Gilyazova, А. С. Карунас, Э. К. Хуснутдинова, O. N. Savelieva, I. M. Khidiyatova
article en
1 citations

Abstract

Asthma is a common complex disease with susceptibility defined through an interplay of genetic and environmental factors. Responsiveness to asthma treatment varies between individuals and is largely determined by genetic variability. The polygenic score (PGS) approach enables an individual risk of asthma and respective response to drug therapy. PGS models could help to predict the individual risk of asthma using 26 SNPs of drug pathway genes involved in the metabolism of glucocorticosteroids (GCS), and beta-2-agonists, antihistamines, and antileukotriene drugs associated with the response to asthma treatment within GWAS were built. For PGS, summary statistics from the Trans-National Asthma Genetic Consortium GWAS meta-analysis, and genotype data for 882 individuals with asthma/controls from the Volga-Ural region, were used. The study group was comprised of Russian, Tatar, Bashkir, and mixed ethnicity individuals with asthma (<i>N</i> = 378) aged 2-18 years. and individuals without features of atopic disease (<i>N</i> = 504) aged 4-67 years from the Volga-Ural region. The DNA samples for the study were collected from 2000 to 2021. The drug pathway genes' PGS revealed a higher odds for childhood asthma risk (<i>p</i> = 2.41 × 10<sup>-12</sup>). The receiver operating characteristic (ROC) analysis showed an Area Under the Curve, AUC = 0.63. The AUC of average significance for moderate-to-severe and severe asthma was observed (<i>p</i> = 5.7 × 10<sup>-9</sup>, AUC = 0.64). Asthma drug response pathway gene variant PGS models may contribute to the development of modern approaches to optimise asthma diagnostics and treatment.

International Journal of Molecular SciencesVol. 26(1)
St Petersburg University (RU), University of Surrey (GB), Ufa Institute of Chemistry (RU), Bashkir State Medical University (RU)
Saint Petersburg State University, Ministry of Science and Higher Education of the Russian Federation
Good health and well-being
Openalex Percentile: Top 34%
Asthma and respiratory diseases
0.33
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